Start with a dataset in Motherduck and build a production-ready analytics app using Omni’s semantic model and APIs. We’ll cover practical data modeling techniques, share lessons learned from building AI features, and walk through how to give AI the context it needs to answer questions accurately. You’ll leave with a working app and the skills to build your next one.

Every sprint consumed by fixing parsers is a sprint spent not shipping product- brittle parsing kills velocity. This workshop is about retiring that cycle so you can move from messy, unstructured inputs to production-ready data in seconds. bem ingests and transforms any unstructured input at any volume — PDFs, emails, Excel, Word, CSV, text, JSON, images (PNG, JPEG, HEIC, HEIF, WebP), HTML, and audio (WAV, MP3, M4A) — into clean JSON instantly via API. With primitives like Transform, Join, Split, Route, and Analyze, you define the exact workflow your product needs. Built-in Evals measure + enforce accuracy automatically so quality doesn’t drop as you scale. Flow outputs straight into MotherDuck so you can go from chaos to query without manual cleanup — and your team can focus on shipping, not scraping.

The lakehouse promised to unify our data, but popular formats can feel bloated and hard to use for most real-world workloads. If you've ever felt that the complexity and operational overhead of "Big Data" tools are overkill, you're not alone. What if your lakehouse could be simple, fast, and maybe even a little fun? Enter DuckLake , the native lakehouse format, managed on MotherDuck. It delivers the powerful features you need like ACID transactions, time travel, and schema evolution without the heavyweight baggage. This approach truly makes massive data sets feel like Small Data. This workshop is a practical, step-by-step walkthrough for the data practitioner. We'll get straight to the point and show you how to build a fully functional, serverless lakehouse from scratch. You will learn: The Architecture: We’ll explore how DuckLake's design choices make it fundamentally simpler and faster for analytical queries compared to its JVM-based cousins. The Workflow: Through hands-on examples, you'll create a DuckLake table, perform atomic updates, and use time travel—all with the simple SQL you already know. The MotherDuck Advantage: Discover how the serverless platform makes it easy to manage, share, and query your DuckLake tables, enabling a seamless hybrid workflow between your laptop and the cloud.

Gain a clear understanding of Estuary and its role in real-time data integration. The session will begin with an overview of the platform and how it works, then move into the distinctive advantages that set Estuary apart in today’s data landscape. From there, you’ll explore practical use cases that demonstrate how organizations are leveraging real-time data to drive meaningful outcomes. We’ll close by examining why Estuary has become the leading choice for loading data into MotherDuck, highlighting the speed, reliability, and simplicity it delivers. Gain hands-on experience with Estuary by completing a guided lab exercise: Setting up a source connection and capturing data in real time. Configuring a MotherDuck connection and materializing the data. Moving live, streaming data end-to-end.